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Strong brand, metro location, mid-level generalist data role with broad skillset increases applicant competition.
Core data engineering skills transfer across industries, though financial domain experience is preferred.
Multiple mandatory technical requirements (Snowflake, DBT, AWS, SQL, Python, ETL) increase filter strictness.
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Design and build large-scale data pipelines and platforms (Data Warehouse, Data Lakes) supporting enterprise data integrations.
Develop and maintain ETL/ELT processes using tools like IBM Data Stage, SAP BODS, DBT, and AWS Glue with focus on performance tuning and data governance.
Collaborate across global teams to support critical business functions including Regulatory Reporting, Finance, and Risk via agile delivery and technical support of production incidents.
Experience in designing and building Data Warehouses and Data Lakes with databases like Oracle, Netezza, and SQL Server.
Proficiency in public cloud data platforms especially Snowflake and AWS.
Strong skills in SQL, Python scripting, and ETL/ELT tools (IBM Data Stage, SAP BODS, DBT, AWS Glue).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in enterprise data platform development in financial services or regulated industries preferred.
Comfortable working in an Agile environment with cross-functional global teams, primarily US time zones.
Demonstrated ability in performance tuning, data governance, and managing complex data pipeline deployments.